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A damper is one of the most important elements in a vehicle suspension system. The damper valves are a fully coupled hydraulic system where the suspension fluid flow interacts with the elastic response of the valve structure. The base valve in the hydraulic damper plays a significant role in compression damping force characteristics of a damper, and therefore designing of the base valve is critical for damping force tuning. In this paper, the impact of the base valve design complexity reduction is quantitatively analyzed. The Current base valve design is restrictive which prevents achieving the required compression damping force ranges without a substantial base valve body parts library. A new base valve assembly is suggested with one more degree of freedom via a restrictor plate. Introducing this new element allows reducing the number of base valve designs for damping performance tuning.

Suspension is an important chassis part which is vital to ride comfort [1]. However, it is difficult to achieve our targeted comfortability level in a short time. Therefore, improving efficiency of damper development is our primary challenge. We have launched a project which aims to reduce the workload on developing dampers by introducing analytical approaches to the improvement of ride comfort. To be more specific, we have been putting effort into developing the damping force prediction, the vehicle dynamics prediction and subjective rating prediction. This paper describes subjective rating prediction method which output a subjective rating corresponding to the physical value of the vehicle dynamics with deep learning. As a result of verification using objective data which was not used for learning process, DNN (Deep Neural Network) prediction method could fairly precisely predict subjective rating of the expert driver.

Semi-active suspension systems have traditionally used accelerometers mounted on the wheel and body to sense vehicle motion. However, the cost and weight of these sensors and their associated bracketry and wiring must be considered when deciding to adopt a semi-active suspension system on a particular vehicle. In previous report [1], Authors have described a Bi-Linear Optimal control algorithm [2] by which sprung mass motion is estimated using height sensor signals and a Kalman filter. Such an algorithm would eliminate the need for additional accelerometers and their associated hardware, resulting in a cheaper and lighter system. In this report, the Authors propose a method of improved ride comfort and reducing tuning time of this algorithm by improving the sprung mass motion estimation method.

Predicting the vibration of a motor gearbox assembly driven by a PWM inverter in the early stages of development is demanding because the assembly is one of the dominant noise sources of electric vehicles (EVs). In this paper, we propose a simulation model that can predict the transient vibration excited by gear meshing, reaction force from the mount, and electromagnetic forces including the carrier frequency component of the inverter up to 10 kHz. By utilizing the techniques of structural model reduction and state space modeling, the proposed model can predict the vibration of assembly in the operating condition with a system level EV simulator. A verification test was conducted to compare the simulation results with the running test results of the EV.

This paper presents the “Virtual Failure Mode and Effects Analysis (vFMEA)” system, which is a high-fidelity electrical-failure-simulation platform, and applies it to the software verification of an electric power steering (EPS) system. The vFMEA system enables engineers to dynamically inject a drift fault into a circuit model of the electronic control unit (ECU) of an EPS system, to analyze system-level failure effects, and to verify software-implemented safety mechanisms, which consequently reduces both cost and time of development. The vFMEA system can verify test cases that cannot be verified using an actual ECU and can improve test coverage as well. It consists of a cycle-accurate microcontroller model with mass-production software implemented in binary format, analog and digital circuit models, mechanical models, and a state-triggered fault-injection mechanism.

Lightweight metals such as Al and Mg alloys have been increasingly used for reducing mass in both structural and non-structural applications in transportation industries. Joining these lightweight materials using traditional fusion welding techniques is a critical challenge for achieving optimum mechanical performance, due to degradation of the constituent materials properties during the process. Friction stir welding (FSW), a solid-state joining technique, has emerged as a promising method for joining these lightweight materials. In particular, high joining efficiency has been achieved for FSW of various Al alloys and Mg alloys separately. Recent work on FSW of dissimilar lightweight materials also show encouraging results based on quasi-static shear performance. However, coach-peel performance of such joints has not been sufficiently examined.

Highly automated driving systems have a responsibility to keep a vehicle safe even in abnormal conditions such as random or systematic failures. However, creating redundancy in a system to respond to failures increases the cost of the system, and simple redundancy cannot detect systematic failures because some systematic failures occur in each system at the same time. Systematic failures in automated driving systems cannot be verified sufficiently during the development phase due to numerous patterns of parameters input from outside the system. A safety concept based on a “safety sustainer” for highly automated driving systems is proposed. The safety sustainer is designed for keeping a vehicle in a safe state for several seconds if a failure occurs in the system and notifying the driver that the system is in failure mode and requesting the driver to take over control of the vehicle.

It is well known that improving NV performance and weight saving are reciprocity. Brake squeal free is one of the top priority issues during development of brake system. To date, complex eigenvalue analysis has been utilized for prediction of brake squeal. It solves the structural instability problems by modal coupling which is the phenomenon that natural frequencies of normal modes are quite consistent. The positive real parts of complex eigenvalues are identified as instable vibration which causes brake squeal. On the other hand, the needs for light-weight brake system are higher than before due to recent trends of economizing fuel consumption and high driving performance. In order to obtain coexistence of brake squeal free with weight saving, shape optimization technique has been proposed for complex eigenvalue analysis.

New ride control and handling control are developed, and installed in a system using only vehicle height sensor as dedicated sensors and pressure control type semi-active damper. Bi-linear optimal control is applied for controlling ride comfort control constructed observer which is inputted vehicle height sensor for calculating state quantity then used output of the observer. Behavior of vehicle was investigated by vehicle experiment and formalized to further improve the feeling of roll generated by handling control and devised and applied semi-active suspension control method which transiently realize the behavior. Proposed semi-active suspension system not only achieves damping performance as well as skyhook control, but also improves smooth ride comfort and handling performance including roll feeling. In this report, we describe aim, feature and effect of this system.

We have achieved injection quantity range enhancement by using the current waveform control technique for direct injection (DI) gasoline injectors. In this study, we developed an injection quantity simulator to find out the mechanism of non-linear characteristics. We clarified the non-linear production mechanism by using the simulator. This simulator is a one-dimensional simulator that incorporates calculation results from both unsteady electromagnetic field analysis and hydraulic flow analysis into the motion equation of this simulation code. We investigated the relation between armature and the injection quantity by using the simulator. As a result, we clarified that the non-linearity was produced by the bounce of the armature in the opening action. Thus, we found that it is effective to reduce the armature bounce to improve the linearity of the injection quantity characteristics.

In-vehicle networks are generally used for computerized control and connecting information technology devices in cars. However, increasing connectivity also increases security risks. “Spoofing attacks”, in which an adversary infiltrates the controller area network (CAN) with malicious data and makes the car behave abnormally, have been reported. Therefore, countermeasures against this type of attack are needed. Modifying legacy electronic control units (ECUs) will affect development costs and reliability because in-vehicle networks have already been developed for most vehicles. Current countermeasures, such as authentication, require modification of legacy ECUs. On the other hand, anomaly detection methods may result in misdetection due to the difficulty in setting an appropriate threshold. Evaluating a reception cycle of data can be used to simply detect spoofing attacks. However, this may result in false detection due to fluctuation in the data reception cycle in the CAN.

The purpose of this study is to develop model-based methodologies which employ thermo-fluid dynamic engine simulation and multiple-objective optimization schemes for engine control and calibration, and to validate the reliability of the method using a dynamometer test. In our technique, creating a total engine system model begins by first entirely capturing the characteristics of the components affecting the engine system's behavior, then using experimental data to strictly adjust the tuning parameters in physical models. Engine outputs over the full range of engine operation conditions as determined by design of experiment (DOE) are simulated, followed by fitting the provided dataset using a nonlinear response surface model (RSM) to express the causal relationship among engine operational parameters, environmental factors and engine output. The RSM is applied to an L-jetronic® air-intake system control logic for a turbocharged engine.

To detect difficult-to-find defects in automotive control systems, we have proposed a modeling method with a program slicing technique. In this method, a verifier adjusts the boundaries of source code to be extracted on a variable dependence graph, in a kind of data flow. We have developed software tools for this method and achieved a 35% decrease in total verification time on model checking. This paper provides some consideration on effective cases of the method from verification practices. There are two types of malfunction causes: one is the timing of processes (race conditions), and the other is complex logics. Each type requires different elements in external environment models. Furthermore, we propose regression verification based on the modeling method above, to further reduce verification time on model checking. The paper outlines tool extensions needed to realize regression verification.

We have developed a model-based control for the air intake system in a variable valve engine, employing total engine simulation, the response surface method and multi-objective optimization scheme. In our technique, we performed the simulation model tuning and validation, followed by the creation of a dataset for the polynomial regression analysis of the charging efficiency. A D-optimal design, robust least squares method, and likelihood-ratio test were demonstrated to yield a robust and accurate control model. Coupling the total engine simulator with a genetic algorithm, model based calibration for optimal valve timing stored in lookup table was carried out under multiple objectives and restrictions. The reliability of the implementation control model, which considers the effect of gas dynamics in the intake system, was confirmed using a model-in-the-loop simulation.

In response to the growing demand for fuel economy, we are developing a high-efficient variable displacement pump for hydraulic power steering systems. In order to develop a quiet variable displacement pump which generates lower noise for better vehicle interior sound quality, we have been developing a simulation tool which includes hydraulic analysis, vibration analysis, and vehicle interior noise analysis which combines simulation outputs and measured noise transfer functions of the targeted vehicle. This paper provides both validation results of the simulation tool and application examples to design improvement to conclude the effectiveness of the simulation tool developed.

Experiments were carried out to study the effect of thermal expansion of the tool during Friction Stir Spot Welding (FSSW) of large commercial automotive grade aluminum sheets. The objective of this study was to evaluate the tool “growth” using both experimental and numerical techniques and to see its effect on the weld quality (measured in terms of static strength). Two hundred friction stir spot welds were made over 25 Al sheets (A6022-T4) with a specific time interval between each sheet, thereby trying to simulate the welding conditions/sequence on a production line. An Infrared (IR) camera was used to monitor the temperature gradient on the tool during the welds. In addition, finite element analysis was run to predict the thermal expansion of the tool based on the temperature boundary conditions obtained from the IR camera during the experiment.

A numerical simulation technique was implemented to automatically optimize the plunger velocity to reduce the defects occurring during die-casting by considering the number of free surfaces and potential energy of the molten metal. In pressure die-casting, the most common defect is porosity that is formed by air entrapment in the following two stages - the first is the injection of the molten metal into shot sleeve, and the second is the filling of the molten metal into the cavity. The latter phenomenon has been investigated in detail by various numerical simulation codes, but there is limited information concerning the former. In order to the simulate flow pattern in the shot sleeve, a moving boundary method is incorporated into the conventional filling simulation system. In addition, the plunger speed and the acceleration time for the various pre-filled levels of molten metal in the sleeve are determined by automatic optimization.